Patent application title: System and Method for Developing Loss Assumptions

Abstract:

A method for developing assumptions for use in evaluating the possible
occurrence of an event comprises the steps of defining a plurality of
factors correlated with each other to the event, assigning a plurality of
levels to each factor, determining a relative occurrence rate for
selected combinations of factors and levels, and assigning selected
combinations to one of a plurality of cohorts. In certain embodiments,
the method, and a corresponding system are used in designing an insurance
product. The method may include the additional steps of assigning values
to the levels and evaluating expected performance of the product based
upon the values assigned to the levels and the expected loss
distribution. The step of producing an expected loss distribution
includes determining, for at least some of the selected combinations, a
cumulative probability of occurrence, and determining, for at least one
of the selected combinations, an incremental probability of occurrence.

Claims:

1-11. (canceled)

12. A system for developing loss assumptions for use in designing an
insurance product, comprising:a correlation unit configured to correlate
a plurality of risk factors with each other to an insurable event;an
assigning unit configured to assign a plurality of levels to each risk
factor indicative of possible states of occurrence in a non-cumulative
manner, and configured to assigna plurality of values to the respective
levels;a producing unit configured to produce an expected loss
distribution for selected combinations of said risk factors and levels;
andan evaluation unit configured to evaluate the expected performance of
the insurance product based upon the values assigned to the levels and
the expected loss distribution.

13. The system according to claim 12, wherein the producing unit further
comprises:a first determination unit configured to determine a cumulative
probability of occurrence for selected combinations of said risk factors
and levels in a population;a second determination unit configured to
determine an incremental probability of occurrence for at least some of
said selected combinations of said risk factors and levels in a
population; anda third determination unit configured to determine a loss
rate for said selected combinations.

14. The system according to claim 13, wherein the producing unit
comprises:a multiplication unit to multiply the incremental or cumulative
probability of occurrence for each of said selected combinations times
the respective loss rate.

15. The system of claim 12, wherein the evaluation unit is further
configured to evaluate an expected loss rate of the product.

16. The system of claim 12, wherein the evaluation unit is further
configured to evaluate an expected market share to be obtained by the
product.

17. The system of claim 12, further comprising:an adjustment unit
configured to adjust at least one of the values assigned to each of the
levels based upon an evaluation of the expected performance of the
insurance product.

18. The system of claim 12, further comprising a plurality of cohorts,
each cohort representing a range of incremental probabilities of
occurrence of the insurable event.

19. The system of claim 12, further comprising:an adjustment unit
configured to adjust the values assigned to each of the levels and
re-evaluating the expected performance of the insurance product.

20. The system of claim 12, wherein the number of said plurality of risk
factors is three or more.

21. The system of claim 12, wherein a number of said plurality of risk
factors used is between 8 and 64.

22. The system of claim 12, wherein said assigning unit is configured to
assign numerical values to each of the respective levels.

Description:

RELATED APPLICATIONS

[0001]The present application is a continuation patent application which
is related to and claims priority to U.S. Divisional patent application
Ser. No. 11/968,996 filed Jan. 3, 2008; which is related to and claims
priority to U.S. patent application Ser. No. 10/291,301 filed Nov. 8,
2002 which claims priority to U.S. Provisional Patent Application Ser.
No. 60/334,261, filed on Nov. 29, 2001, all entitled System and Method
for Developing Loss Assumptions. The subject matter disclosed in said
utility and provisional applications is hereby expressly incorporated
into the present application.

FIELD OF INVENTION

[0002]This invention relates generally to risk management and, more
specifically to the field of financial products. More particularly, this
invention relates to systems and methods for developing and assessing
assumptions used in designing and pricing financial products, including
insurance products.

BACKGROUND AND SUMMARY OF THE INVENTION

[0003]The pricing of insurance products is difficult because the pricing
must be done before the product is sold, but must reflect results that
will not be known for some time after the product has been bought and
paid for. With tangible products, "the cost of goods sold" is known
before the product is sold because the product is developed from raw
materials which were acquired before the product was developed. With
insurance products, this is not the case. The price of the coverage is
set and all those who buy the coverage pay the premium dollars.
Subsequently, claims are paid to the unfortunate few who experience a
loss. If the amount of claims paid is greater than the amount of premium
dollars collected, then the insurer will make less than their expected
profit and possibly lose money. If the insurer has been able to predict
the amount of claims to be paid and has collected the right amount of
premiums, then the insurer will be profitable.

[0004]The price of an insurance product is determined from a set of
assumptions related to expected losses, expenses, investments, etc.
Generally, the largest amount of money paid out by an insurer is in the
payment of claims for loss. Since the actual amounts will not be known
until the future, insurers make assumptions about what the losses will
be. If the actual claims payments are less than or equal to the predicted
claims payment, then the product will be profitable. If the actual claims
are greater than the predicted claims in the assumptions set in pricing,
then the product will not be profitable and the company will lose money.
Hence, the ability to set assumptions for the expected losses is critical
to the success of the product. The present invention has been developed
to assist in this process of developing and assessing assumptions for
pricing insurance products.

[0005]An insurer must develop a set of assumptions which reflect the
probabilities of occurrence of the loss being insured, the probability of
the number of people who will lapse the coverage (that is, stop paying
their premiums), and other financial elements such as expenses, interest
rates and taxes. Insurers use historical data on losses to help them
predict what future losses will be. Professionals with experience in
mathematics and statistics called actuaries develop tables of losses that
incorporate the rate of loss for the group over time into cumulative loss
rates. These tables of cumulative loss rates are the bases for pricing
insurance products.

[0006]In pricing a specific product, an actuary starts with the basic loss
tables. Then, based upon judgments concerning the specific nature of the
table, the risk to which it is applied, the design of the product, the
risk selection techniques applied at the time the policy is issued, and
other factors, the actuary develops a set of assumptions for the
cumulative loss rates to serve as the foundation for the expected future
claims of the product.

[0007]Depending upon the specific insurance product being developed, the
historical data and the loss tables do not always correlate well with the
specific risks which the policy will cover. For example, most life
insurance mortality tables deal with the average probability of death in
an insured population. However, some insurance products are directed to
sub-groups in a population. Mortality may vary in these sub-groups. For
example, some healthier people have a mortality which is preferred, that
is, better than the average mortality. In order to price products for
such people, actuaries must be able to segment the cumulative loss rate
from the standard mortality tables into cohorts to tease out the
mortality of those who are objectively healthier within the standard
group, and to develop assumptions on these more specific subsets of the
population.

[0008]Segmenting these cumulative loss rates requires that the actuary
understand the risk factors for loss which characterize the general
insured population versus the risk factors which signal the subset with
preferred mortality. For example, in life insurance, people with no
medical conditions and a blood pressure measurement at the high end of
the normal range may have standard mortality, while those with a blood
pressure measurement at the lower end of the normal range may have
preferred mortality, i.e., a lower mortality rate.

[0009]However, the standard loss tables do not take into consideration
these separate risk factors. Actuaries must research other sources of
data, such as medical or epidemiological studies to determine loss rates
of specific populations and the risk factors which are correlated with
them. Then, in the process of pricing a product which differentiates
price based upon the risk factors, the actuary must set assumptions as to
how these risk factors correlate with the cumulative loss rates in the
loss table. Going back to the previous example, if the product is sold to
healthy individuals with a blood pressure in the lower end of the normal
range, the actuary must make an assumption of how much less than the
standard mortality the mortality rate will be for this subset to
determine the premium price for this subset of people.

[0010]Further, in the creative design of products, actuaries will have to
develop the appropriate assumptions of loss in which there may be
multiple risk factors, each one, individually or in combination with
other factors, derived from different studies and loss tables.

[0011]Certain embodiments of the present invention allows the user to take
individual, or various combinations of risk factors and associated loss
rates from different studies, and use these risk factors and loss rates
to unbundle the components of cumulative loss in the loss tables. Some
embodiments further allow the user to create new relationships among the
risk factors, and determine new cumulative loss rates reflecting the new
sets of risk factors.

[0012]The present invention has multiple applications. New insurance
products can be designed with a large number of risk factors, all of
which can be correlated as to their contribution to a cumulative loss
rate. A wide range of existing and new types of product designs and
specifications can be accurately correlated with the loss assumptions
used in actually pricing an insurance product by analyzing the involved
risk factors in a positive or negative manner. This invention also helps
to define the pricing implications of making exceptions in accepting
risks which may not have all of the risk factors in line with those used
in setting the assumptions.

[0013]One embodiment of the present invention comprises a method for
developing loss assumptions for use in designing an insurance product.
The method comprises steps of defining a plurality of factors correlated
to an insurable event, assigning to each factor a plurality of levels
indicative of possible states of occurrence, assigning values to each of
the levels, producing an expected loss distribution for selected
combinations of the factors and levels, and evaluating the expected
performance of the insurance product based upon the values assigned to
the levels and the expected loss distribution. In one embodiment, the
expected loss distribution is produced by the steps of determining, for
the selected combinations of factors and levels, an incremental
probability of occurrence of each combination in a population, and
determining, for these selected combinations, a loss rate. This loss rate
reflects the factors present at the time the policy is issued. There are
significant correlation effects with the presence of various combinations
of factors. The expected loss distribution is the product of these two
quantities.

[0014]The step of evaluating the expected performance of the insurance
product may comprise the step of evaluating an expected loss rate of the
product, an expected market share to be obtained by the product, and/or
other aspects of the product. In one embodiment, at least one of the
values assigned to the levels is adjusted based upon the evaluation, and
the expected performance of the product is re-evaluated based upon the
adjusted levels.

[0015]Certain embodiments of the invention further include the steps of
defining a plurality of cohorts with each cohort representing a range of
incremental probabilities of occurrence of the insurable event.

[0016]Another embodiment of the invention is a method for developing loss
assumptions for use in designing an insurance product for a population of
risks comprising the steps of defining a plurality of factors correlated
to an insurable event, assigning to each factor a plurality of levels
indicative of possible states of occurrence of the factor in the
population, determining, for selected combinations of factors and levels,
a loss distribution based upon an incremental probability of occurrence
of the combination in the population and a respective loss rate and
assigning the selected combinations to one of a plurality of cohorts. One
embodiment comprises the additional steps of assigning values to each of
the levels, and evaluating the expected performance of the insurance
product based upon the values assigned to the levels and the expected
loss distribution. The step of evaluating the expected performance of the
insurance product comprises the step of evaluating an expected loss rate
for the product, an expected market share to be obtained by the product,
and/or other aspects of the product. One embodiment of the invention
comprises the additional step of adjusting at least one of the values
assigned to the levels based upon the evaluation of the expected
performance of the insurance product. The product may be re-evaluated
with the adjusted values and additional adjustments to the values may be
made, as desired.

[0017]The present invention may be used in connection with financial
products other than insurance products, such as mortgages, loans and
similar products. Accordingly, one embodiment of the invention is a
method for developing assumptions for use in designing such products.
This embodiment comprises the steps of defining a plurality of factors
correlated to an event, characteristic, feature or other aspect of the
financial product, assigning a plurality of levels to each factor
indicative of possible states of occurrence of the factor in a
population, assigning values to each of the levels, determining, for
selected combinations of factors and levels, a distribution based upon an
incremental probability of occurrence of the combination in the
population, and evaluating the expected performance of the financial
product based upon the values assigned to the levels in the distribution.
In the case of a mortgage, for example, factors may include income level,
price range of the property, term, credit rating of the mortgagee, etc.
Each of these and/or other factors may be assigned a plurality of levels
indicative of possible states of occurrence of such factors in a
population.

[0018]In one embodiment, the step of evaluating the expected performance
of a financial product may include the step of evaluating an expected
loss rate for the product or evaluating an expected market share to be
obtained by the product. One embodiment further comprises the additional
step of adjusting at least one of the values assigned to each of the
levels based upon the evaluation of the expected performance of the
financial product. One or more of the values may be adjusted, and the
product may be re-evaluated, as desired.

[0019]More broadly, the subject invention may be used for managing risk by
developing assumptions for use in evaluating the possible occurrence of
an event. One embodiment includes a method for managing such risk,
comprising the steps of defining a plurality of factors correlated to the
event, assigning a plurality of levels to each factor, assigning values
to each of the levels, determining, for selected combinations of factors
and levels, a probability distribution based upon an incremental
probability of occurrence of the combination in the population and a
relative occurrence rate and assigning the selected combinations to one
of a plurality of cohorts.

[0020]Other advantages and novel features of the present invention will
become apparent from the following detailed description of the invention
when considered in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0021]FIG. 1 illustrates the manner in which levels and values are
assigned to a plurality of factors which are correlated to an insurable
event, and which are considered in developing loss assumptions for use in
the design of an insurance product.

[0022]FIG. 2 illustrates the manner in which a table may be constructed
within the system to account for all possible combinations of factors and
levels selected for use in the design of an insurance product.

[0023]FIG. 3 illustrates a three-dimensional version of a cumulative
probability of occurrence matrix.

[0024]FIG. 4 illustrates a three-dimensional version of a cumulative
mortality ratio matrix.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

[0025]The present invention relates to systems and methods for use in risk
management.

[0026]An application of the present invention is the design and pricing of
financial products. A more specific application of the present invention
relates to systems and methods for designing and pricing insurance
products. The particular embodiments of the invention described in detail
below include a system and method for developing and assessing
assumptions used in the design and pricing of insurance products.

[0027]A loss assumption is a statement relating, directly or indirectly,
to an insurable event which is taken to be true. The design and price of
an insurance product is determined, in large part, from a set of such
assumptions. Loss assumptions may be expressed in numerical terms. With
respect to factors which have been shown by experience to be correlated
with the occurrence of an insurable event, the relationship between a
factor and the insurable event and/or other factors can be quantified.
Quantification allows for the use of statistical and other mathematical
techniques to be brought to bear in the development of assumptions
underlying the design and pricing of a particular insurance product.

[0028]For purposes of illustration, much of the following discussion is
specific to life insurance as a specific category of insurance product,
and mortality as a specific category of risk. However, it should be
clearly understood that the system(s) and method(s) disclosed are
applicable in other product and risk categories. Thus, the present
disclosure should not be construed as limited in any way to the
particular field of life insurance or mortality.

[0029]Specifically, the systems and methods of the present invention can
be used in any field in which a decision must be made, and in which a
plurality of factors can be identified as being correlated with the
occurrence of an event or condition related to the decision. For example,
in the design of a mortgage (or other type of loan product), decisions
must be made as to interest rate, points payable in advance, maximum loan
amounts, loan default rates and other factors. The loan default rate may
be influenced by factors specific to each transaction, such as the
income/asset level of a prospective borrower, the type of property,
prevailing market conditions, risk tolerance of the lender, and other
factors. The systems and methods of the present invention may be used to
design a mortgage product and/or to facilitate the decision process in
transactions involving such product. Other examples will be readily
apparent to those of skill in the art of risk management and decision
making in the presence of risk.

Life Insurance Example

[0030]In the design and pricing of life insurance products, insurers
define risk classifications or "bands" into which members of an insurable
population can be placed. Defining the effects on the loss (mortality)
rate of various combinations of risk classifications (i.e., banding or
stratifying the risk) is an actuarial function. Evaluating the risk of a
specific individual or risk to determine which classification the
individual or risk fits in is an underwriting function.

[0031]In the case of a specific risk (e.g., an individual life in the life
insurance context), it is generally impossible to determine exactly when
an insurable event will occur. However, insurers can develop a risk
profile for an individual risk which may be used to determine how likely
an occurrence of the insurable event is at a particular time. Risk
profiles are developed on the basis of factors which are both
quantifiable and verifiable. In the case of life insurance, blood
pressure, cholesterol levels, and build are quantifiable and verifiable
factors which may be used to develop a risk profile. In the design and
pricing of a life insurance product, an insurer makes assumptions as to
the relative impacts of such factors on mortality, and creates risk
classifications and pricing structures based upon these assumptions.

[0032]The present invention facilitates the development of risk
classifications or "cohorts" in the design of an insurance product. FIG.
1 illustrates the manner in which one embodiment of the method and system
of the present invention is used in the context of life insurance. In
this embodiment, the first step is defining a plurality of factors that
are correlated to the insurable event. In the particular example
illustrated in FIG. 1, these are listed in the column titled FACTORS as
SP (systolic blood pressure), DP (diastolic blood pressure), CH
(cholesterol level), and CH RATIO (cholesterol ratio). There are
additional factors (e.g., build, motor vehicle record, family history,
past medical history, and hobbies) which may be considered, as well. It
is not unusual to consider as many as twelve to fifteen factors. However,
it is also possible to use a lesser or greater number of factors (such
as, two or forty). In the system and method of the present invention, an
insurer or other client for whom a product is being developed can specify
which and how many factors are to be used, and the levels at which
individuals qualify under each factor. In some instances, one or more
factors may be highly correlated with one another. In such instances, use
of both factors is somewhat redundant and has only a limited impact upon
the process of defining risk classifications or cohorts. Use of this
system and method facilitates evaluation and selection of factors by
insurers or other clients.

[0033]The next step in the process as illustrated in FIG. 1 is assigning
levels to each of the factors. This is illustrated in FIG. 1 in the
column titled LEVELS. The number of levels listed and the associated
values and ranges are illustrative only. More (or fewer) levels may be
used and the values and ranges associated therewith may be varied.
However, an aspect of the present invention is that the levels are chosen
and associated with the expected ranges in a manner which is
non-cumulative. That is, the applicable population (and its associated
mortality) is spread over the levels, as opposed to each successive level
being inclusive of all preceding levels. For example, with reference to
factor SP, mortality for a population may be spread over levels 1, 2, 3
and 4 in the example of FIG. 1 as 15%, 35%, 40% and 10%, respectively,
rather than cumulatively as 15%, 50%, 90% and 100%. This distinction is
discussed in additional detail below.

[0034]The next step in the process as illustrated in FIG. 1 is assigning
values (in this case, debits and credits) to each of the levels. This is
illustrated in FIG. 1 in the column titled (DEBITS)/CREDITS by
appropriately weighting the values assigned to each of the levels and
factors. The relative impact of each level and factor may be adjusted to
finely tune the system for use in the actuarial process of defining risk
classifications, as well as in the underwriting process of evaluating
specific risks. This approach further facilitates accounting for
interrelationships among the various factors. For example, the debits
assigned to an individual having a high cholesterol may be at least
partially (and incrementally) offset by credits resulting from a
favorable cholesterol ratio, blood pressure or build factor. Assigning
numerical values to the various levels facilitates consideration of such
interrelationships, particularly in the environment of digital
processing.

[0035]The user of the system (e.g., an insurer or the designer of an
insurance product for an insurer) is usually involved in the selection of
factors, designation of levels, and assignment of values in the process
described thus far. Indeed, in some cases, an insurer who will be
offering the product in the market place will have the primary role in
this regard. In addition to the insurer's own knowledge base, beliefs and
preferences concerning the relative impacts of the various factors and
levels on mortality, other considerations may dictate or influence the
choice of factors and levels, and the relative values assigned to the
levels. For example, an insurer may choose, for competitive reasons, to
emphasize (or de-emphasize) certain factors. A product may be designed,
at least in part, to achieve a certain market share in a given
population. The choice of factors, levels and values may also be impacted
by the existence of other competitive products in the market. FIG. 2
illustrates the manner in which a table may be constructed within the
system to account for all possible combinations of factors and levels
selected for use in the design of a particular product. In the example of
FIG. 2, 5 factors are designated, with the factors having 5, 6, 8, 9 and
10 levels, respectively. Again, the number of factors and levels are
illustrative only. Both the number of factors and the number or levels
for each factor may be increased or decreased, as desired.

[0036]For each of the combinations represented by the rows in FIG. 2, two
quantities are determined and entered into the system. The first quantity
is a probability of occurrence of each combination within a standard
population. The second quantity is a mortality ratio (i.e., the number of
observed deaths divided by the number of expected deaths) for each
combination. Information regarding these quantities is available from
empirical data and research. Much of this information is available in the
public literature, while some will be available to insurers based upon
their experiences with individuals and groups. For some combinations, the
combined judgment of actuaries and other professionals may form the
primary basis for one or the other of these two quantities. In any event,
as additional information (e.g., studies, research results, experiences
with particular groups and individuals, etc.) becomes available, that
information may be used to continuously refine these quantities. The
product of the probability of occurrence and the mortality ratio is a
mortality distribution for all the combinations.

[0037]When using large numbers of factors and levels, there will
inevitably be combinations for which relatively little information is
available from which to determine the probability of occurrence and/or
mortality ratio. Thus, there will be "gaps" occurring throughout the
table. Interpolation may be used to bridge such gaps. However, simple
interpolation may lead to irrational results (i.e., for certain
combinations, the system may produce results which are contrary to logic
and experience). This result is, for the most part, avoided by use of an
incremental (rather than cumulative) approach in determining the
mortality distribution for the combinations. As described above in
connection with designating the levels of FIG. 1, the mortality
distribution for each combination is based on incremental mortality
changes (i.e., the "delta") between various levels, rather than
cumulatively as might otherwise be done.

[0038]As previously discussed, a probability of occurrence can be
determined for each of the combinations illustrated in FIG. 2. These
values can be arranged in the form of the matrix having dimensions equal
to the number of factors being considered. For instance, the example of
FIG. 2 would result in a five dimensional matrix. As also previously
discussed, the values representative of probability of occurrence can be
presented in two formats, cumulative or incremental. Each of the values
in the latter format may be termed "splinters."

[0039]The cumulative matrix provides the values in the form that the
probability of occurrence provided is the one that satisfies or exceeds
the criterion for each of the factors. The mortality ratio under this
approach provides the overall average relative mortality of the group
that satisfies or exceeds the criterion for each of the combination of
factors. This structure is easier to use when translating research
results into the matrix format. However, as the number of combinations of
factors and levels increase, it becomes increasingly more difficult to
ensure that each of the micro or local relationships between adjacent
cells is consistent in all dimensions. As a result, the number of factors
that can be included in one cohort is limited. This structure allows for
a preferred insurance program where qualification must be based on
meeting all criteria, with or without a limited number of possible
exceptions.

[0040]The incremental or splinter matrix provides the values in the form
that the probability of occurrence provided is the one that exactly meets
the criterion of each of the combinations. The mortality ratio provides
the relative mortality of the group that exactly meets the criteria for
all of the specific criteria in that combination of factors. It is easier
to work with this format to ensure that all of the relative relationships
are consistent. It is also easier to make adjustments to the factors,
including the adjustment for varying relationships in different
countries. Using this structure, a larger number of factors can be used
for each cohort. This approach also makes possible the pricing of a
product using debits and credits as the qualifying criteria. "Exception
rules" under the "meeting all criteria" approach are simplified.

[0041]There is a relationship between the cumulative and splinter formats.
That relationship is:

[0042]Matrices and dimensions greater than three are inherently hard to
visualize. However, a three dimensional version of the cumulative
probability of occurrence matrix appears in FIG. 3. FIG. 4 illustrates
the corresponding cumulative mortality ratio matrix. In accordance with
the above relationships, the corresponding splinter matrices may be
derived. An illustrative example of this calculation is:

[0043]Similar calculations can be performed to derive each term of the PS
and MS matrices.

[0044]The product of the probability and mortality ratio yields a
mortality distribution for all possible combinations in the table of FIG.
2. The mortality distribution is used to evaluate the values assigned by
the user. This evaluation allows the user to appreciate the consequences
of decisions made regarding the factors and levels selected and the
values assigned (e.g., the debits/credits of FIG. 1) as they relate to
projected pricing and profitability of the product, the market share to
be obtained by the product, and other considerations which are of
importance in product design. A sensitivity analysis can be performed, if
desired, by varying certain of the values assigned to various factors and
levels, and determining the manner in which these values impact these
considerations. This process allows the user to refine the design of the
product to accomplish commercial goals, while having a more complete
understanding of the projected performance of the product.

[0045]It should be noted that the values assigned to each of the
combinations in the table of FIG. 2 may be represented by a numerical
quantity (for example, the cumulative debits and credits for each
combination). In such an arrangement, the numerical quantities will not
necessarily be unique. For example, an individual represented by the
combination of 23225 may have the same overall numerical quantity or
"score" as an individual represented by the combination 31323. These
scores provide the user with a means for drawing "lines" through the
multi-dimensional tables to determine which combinations may qualify for
particular coverages. If two individuals represented by different
combinations have the same score, as referenced above, the overall debits
and credits associated with each of these combinations may allow both
individuals to qualify for a particular coverage.

[0046]It should also be noted that the system will also allow for
assigning an alternative value to one of the factors based on one or more
of the other levels. For example, an individual represented by a 22125
combination may be viewed differently, with respect to the build factor,
than an individual represented by a 44435 combination. A lower (or
higher) value may be assigned to build level 5 in the former case, as
compared to that assigned in the latter. In other words, the significance
of a relatively high "build" factor may be increased when it coincides
with relatively high blood pressure and cholesterol levels. Other
relationships between the various factors may be similarly addressed.

[0047]Throughout this description and the accompanying claims, the terms
"correlation" and "correlated" are used (e.g., "a plurality of factors
correlated to an insurable event"). These terms are not used in the
narrow mathematical sense of a particular second order moment of a
probability distribution. Rather, these terms are used in a sense
intended to indicate the presence of, or a measure of, the dependence
between two or more variables.

[0048]Although the invention has been described and illustrated in detail,
it is to be clearly understood that the same is intended by way of
illustration and example only and is not to be taken by way of
limitation. The spirit and scope of the invention are to be limited only
by the terms of the appended claims.